Access Type

Open Access Dissertation

Date of Award

January 2010

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Mathematics

First Advisor

George G. Yin

Abstract

In this dissertation we investigate asymptotic properties of Markov modulated random processes having two-time scales. The model contains a number of mixing sequences modulated by a switching process that is a discrete-time Markov chain. The motivation of our study stems from applications in manufacturing systems, communication networks, and economic systems, in which regime-switching models are used.

This thesis focuses on asymptotic properties of the Markov modulated processes under suitable scaling. Our main effort focuses on obtaining weak convergence and strong approximation results.

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